Data visualisation system and method

ABSTRACT

A data visualisation system is disclosed that includes a data value memory, a display, and contour generator. The data value memory maintains a finite set of data values. The display is arranged to display a representation of each data value centered on respective data points. The contour generator is arranged to generate and display a representation having a cross-sectional shape of a bell-shaped curve in which each data point is displayed as an apex of the bell-shaped curve. Also disclosed is a method of data visualisation and a data visualisation computer program.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is a continuation of U.S. patent application Ser. No.12/185,004, filed Aug. 1, 2008, which is a continuation of U.S.application Ser. No. 10/910,963, filed Aug. 4, 2004, now U.S. Pat. No.7,668,726, issued Feb. 23, 2010, which is a continuation of U.S. patentapplication Ser. No. 09/674,469, filed Feb. 21, 2001, which claims thebenefit of foreign priority under 35 U.S.C. 371 of PCT/NZ00/00099, filedJun. 14, 2000, the disclosures of which are herein incorporated byreference in their entirety.

COPYRIGHT NOTICE

A portion of the disclosure of this patent document contains materialthat is subject to copyright protection. The copyright owner has noobjection to the facsimile reproduction by anyone of the patent documentor the patent disclosure, as it appears in the Patent and TrademarkOffice patent files or records, but otherwise reserves all copyrightrights whatsoever.

FIELD OF DISCLOSURE

The disclosure relates to a data visualisation system and method.

BACKGROUND

The low cost of data storage hardware has led to the collection of largevolumes of data. Merchants, for example, generate and collect largevolumes of data during the course of their business. To competeeffectively, it is necessary for a merchant to be able to identify anduse information hidden in the collected data. This data could includeshop floor sales, and where the merchant operates a website, the usethat is made of a website may also be collected. The task of identifyingthis hidden information has proved very difficult for merchants.

It is also important for other individuals and organisations to analysestored data. Each time a game of sport is played, there is generally alarge volume of data collected. For example, a game of rugby uniongenerates statistics such as total number of points scored, the numberof tries scored and the number of tries scored which are then converted.There is an increasing trend toward analysis of collected data with aview to analysing opponent strategies and as a coaching aid in assessingthe strengths and weaknesses of a particular team. It is also especiallydesirable with televised sports to present the collected data tospectators in a form which is easily interpreted.

Traditionally, analysis of data has been achieved by running a query ona set of data records stored in a database. The merchant or other partyfirst creates a hypothesis, converts this hypothesis to a query, runsthe query on the database, and interprets the results obtained withrespect to the original hypothesis.

One disadvantage of this verification-driven hypothesis approach is thatthe merchant must form the desired hypothesis in advance. This is merelyconfirming what the merchant already suspects and does not provide themerchant with information which may be unexpected. Another disadvantageis that the merchant needs to have available the technical knowledge toformulate the appropriate queries.

SUMMARY

In broad terms in one form the invention comprises a data visualisationsystem comprising a data value memory in which is maintained a finiteset of data values; and display means arranged to display a contouredrepresentation wherein one or more of the data values are displayed ascontours around one or more data points, each data value centred on adata point.

In another form in broad terms the invention comprises a method of datavisualisation comprising the steps of: maintaining in a data valuememory a finite set of data values; and displaying a contouredrepresentation wherein one or more of the data values are displayed ascontours around one or more data points, each data value centred on adata point.

In another form in broad terms the invention comprises a datavisualisation computer program comprising a finite set of data valuesmaintained in a data value memory; and display means arranged to displayas contoured representation wherein one or more of the data values aredisplayed as contours around one or more data points, each data valuecentred on a data point.

BRIEF DESCRIPTION OF THE DRAWING

Preferred forms of the data visualisation system and method will now bedescribed with reference to the accompanying figures in which:

FIG. 1 shows a block diagram of a system in which one form of theinvention may be implemented;

FIG. 2 shows the preferred system architecture of hardware on which thepresent invention may be implemented;

FIG. 3 is a preferred representation generated in accordance with theinvention;

FIG. 4 is one view of a data point from the presentation of FIG. 3;

FIG. 5 is a further view of the data point of FIG. 4;

FIG. 6 is a flowchart of a preferred form of the invention;

FIG. 7 is another preferred representation generated in accordance withthe invention;

FIG. 8 shows a block diagram of a system in which another form of theinvention may be implemented;

FIGS. 9 and 10 show preferred form representations generated inaccordance with the invention;

FIGS. 11 to 15 show preferred form representations based on aggregateddata values;

FIGS. 16 to 20 show preferred form representations based on distributeddata values;

FIGS. 21 to 24 show preferred form representations showing directionalinformation of data values relative to each other;

FIG. 25 shows a block diagram of a system in which another form of theinvention may be implemented;

FIG. 26 shows a typical representation generated and displayed by theinvention showing a customer provenance map and merchant storerepresentation;

FIG. 27 shows a further preferred form representation generated anddisplayed by the invention showing the site map of a merchant web site;

FIG. 28 shows the representation of FIG. 27 configured to identifytraffic flow;

FIG. 29 shows a web site usage profile generated and displayed by theinvention;

FIG. 30 shows a preferred form representation generated and displayed bythe invention where the merchant provides financial services;

FIG. 31 is another preferred form representation where the merchantprovides financial services;

FIG. 32 shows a preferred form representation generated and displayed bythe invention where the merchant provides insurance services;

FIG. 33 shows a preferred form representation generated and displayed bythe invention for a manufacturing process;

FIG. 34 is a preferred form database schema for representing sportsdata;

FIG. 35 shows a preferred form representation generated and displayed bythe invention involving sports data;

FIGS. 36 to 38 show further preferred form representations involvingsports data;

FIG. 39 is one preferred method of sports data acquisition; and

FIG. 40 is a further preferred form representation generated anddisplayed by the invention involving carpark operations.

DETAILED DESCRIPTION OF PREFERRED FORMS

FIG. 1 illustrates a block diagram of the preferred system in which oneform of the present invention 12 may be implemented. The system includesone or more clients 20, for example 20A, 20B 20C, 20D, 20E and 20F,which each may comprise a personal computer or workstation describedbelow. Each client 20 is interfaced to the invention 12 as shown inFIG. 1. Each client 20 could be connected directly to the invention 12,could be connected through a local area network or LAN, or could beconnected through the Internet.

Clients 20A and 20B, for example, are connected to a network 22, such asa local area network or LAN. The network 22 could be connected to asuitable network server 24 and communicate with the invention 12 asshown. Client 20C is shown connected directly to the invention 12.Clients 20D, 20E and 20F are shown connected to the invention 12 throughthe Internet 26. Client 20D is shown as connected to the Internet 26with a dial-up connection and clients 20E and 20F are shown connected toa network 28 such as a local area network or LAN, with the network 28connected to a suitable network server 30.

The preferred system 10 further comprises a data repository 40, forexample a data warehouse maintained in a memory. It is envisaged thatthe data repository may alternatively comprise a single database, acollection of databases, or a data mart. The preferred data repository40 includes data from a variety of sources. The data repository mayinclude, for example, interaction data 42 representing interactionsbetween customers and merchants as will be more particularly describedbelow. The data repository may also include data from other sources forexample census data 44, scan data 46 obtained from scanning bar-codes onproducts, data from merchant customer databases 48, data from merchantloyalty programmes 50 and/or promotion data 52 held by a merchant orother organisation.

One preferred form of the invention 12 comprises a personal computer orworkstation operating under the control of appropriate operating andapplication software having a data memory 60 connected to a server 62.The invention is arranged to retrieve data from the data repository 40,process the data with the server 62 and to display the data on a clientworkstation 20, as will be described below.

FIG. 2 shows the preferred system architecture of a client 20 orinvention 12. The computer system 70 typically comprises a centralprocessor 72, a main memory 74 for example RAM and an input/outputcontroller 76. The computer system 70 also comprises peripherals such asa keyboard 78, a pointing device 80 for example a mouse, a display orscreen device 82, a mass storage memory 84 for example a hard disk,floppy disk or optical disc, and an output device 86 for example aprinter. The system 70 could also include a network interface card orcontroller 88 and/or a modem 90. The individual components of the system70 could communicate through a system bus 92.

It is envisaged that the invention have a wide area of application andthe nature and format of the data stored in the data repository 40 willbe different for each application. Different applications of theinvention are set out below. In each case, the invention 12 is arrangedto display a contoured representation of data on a screen display of aclient workstation 20.

FIG. 3 illustrates at 100 one example of a display generated by thesystem where the merchant operates a casino or similar gaming venue. Inthis example, a representation of the merchant is generated anddisplayed. The graphical representation comprises a spatialrepresentation of an area of the casino showing the layout of individualgaming machines and stations, two of which are indicated at 102 and 104respectively. It will be appreciated that the particular representationgenerated will be varied according to the nature of the datarepresented, as will be described below.

The representation 100 is arranged to display the revenue obtained froman individual gaming machine. The revenue for each machine is preferablygraphically represented adjacent or near to the representation of theindividual machine. There are a finite number of machines in the casino,and the individual revenues generated from each machine represent afinite set of data values. These data values are graphically illustratedas data points in the representation 100. For example, the revenue ordata value for machine 102 is graphically illustrated as data point 106and the data value or revenue for machine 104 is graphically illustratedas data point 108.

The preferred representation 100 is colour coded and the value ofrevenue of each machine is illustrated by representing the correspondingdata points in the appropriate colour to represent the correct value ofrevenue of each machine. The areas of the representation 100 around eachdata point are shown as contours. The nature of the contours for eachdata point are preferably represented to gradually drop off or fall awayfrom each data point. Each data point could be represented by X and Yco-ordinates indicating the relative position of each data point in therepresentation. Each data point could also have a Z value representingthe height or magnitude of the data point. This Z value could indicate,for example, the revenue or data value at a particular data point. Eachdata value is therefore centred on a data point.

FIG. 4 illustrates a typical data point, for example data point 106. Thedata value of the data point represents the apex of a bell-shaped curve.As X and Y values in the representation 100 are increased or decreased,the Z value at the new position in the representation will change.

Referring to FIG. 5, data point 106 has an axis 110 and a maximum valueat that axis. At a distance r from the axis 110, the drop in Z value ispreferably calculated by the following drop-off function:

${f(r)} = {\frac{1}{1 + \left( {r/a} \right)}p}$

The value of p is preferably 2 or 3. As the value of p is increased, thedata point is represented having a steeper shoulder and a flatter peakwith steeper walls.

The value of a defines the horizontal distance between the axis 110 andthe point of maximum drop-off of the resulting curve, which in practicedefines the width of the contoured “hill.” The value of a could be, forexample, the point of “half height” of the value. Small values of a willresult in fine detail in a contoured representation and larger values ofa will result in a less detailed representation.

FIG. 6 illustrates the preferred method of operation of the invention12. As shown at 120, data is retrieved from the data repository 40 usinga suitable query. The retrieved data could include data representinginteractions between customers and merchants, where this data is storedin the data repository 40. The retrieved data could include the revenuegenerated by a set of gaming machines over a specified period.

As shown at 122, a set of data values is constructed from the retrieveddata. This set of data values could include for example, revenue valuesgenerated by a set of gaming machines over a trading period.

It is envisaged that the set of data values could be stored in datavalue memory 60 to increase efficiency of the system as indicated at124, which could comprise volatile main RAM or non-volatile mass storageof the work station on which the invention 12 is implemented.

Referring to step 126, the set of data values are retrieved from thevolatile or non-volatile data memory and as shown at 128, a set of datapoints is constructed to represent the data values. Appropriate X and Yvalues are generated for each data point to space the data points over agenerated representation. Z values for each data point are alsocalculated based on individual data values.

Referring to step 130, a contoured representation of the data values isgenerated and displayed on a client workstation 20. The individualdrop-off for each data point is calculated and displayed in theappropriate colour and shading corresponding to the Z value at eachpoint.

It is envisaged that the invention generate individual displays ofcontoured representations. It is also envisaged that the inventiongenerate animated sequences of representations by generating two or more“still” representations at various time interval's and superimposingsuccessive representations over earlier representations to generate ananimated sequence.

As indicated at 132, where such an animated sequence is required,further representations will be needed and if the necessary data isobtainable from the data memory as indicated at 134, it is retrievedfrom the data memory as indicated at 126, otherwise further data isretrieved from the data repository at 120.

In one form the invention is arranged to display data representinginteractions between customers and merchants. Typically, a merchant willoperate in a commercial premises or store from which a customerpurchases goods or services. The merchant may, for example, operate apetrol station in one or more geographic locations. The merchant mayalternatively operate a wagering or betting service, or operate a casinoor other gaming facility in which a number of gaming machines andstations are positioned in one or more rooms at a common venue. Themerchant may also operate a warehouse facility, manufacturing facility,car parking premises, telecommunications network or web site. Themerchant may also offer a range of financial or insurance services.

The merchant does not necessarily need to operate from a commercialpremises or store. For example, the merchant may operate fromstrategically placed machines for example vending machines or amusementmachines. The merchant may also operate a mail order catalogue service,direct market goods or services, or operate from a website or otherelectronic medium. It will be appreciated that the nature of business ofa merchant includes a wide range of activities.

As a customer interacts with a merchant, the interaction generatesinteraction data which is then migrated to the data repository 40. Theinteraction data could be stored in a number of records in a relationaldatabase. Each record may include a merchant identifier used to identifya particular merchant, and where a merchant operates from more than onegeographic location, the merchant identifier or some other identifierincluded in the record may identify the geographic location in which theinteraction occurs.

The record could also include a customer identifier. The merchant may,for example, issue an incentive-supported customer loyalty card which isthen used by the customer during interactions with the merchant. Theloyalty card preferably has stored on it a customer identifier and mayhave stored other data, for example residential address and family sizeof the customer. Such data is stored in loyalty programme database 50and could be migrated to the data repository 40.

Where the merchant operates retail premises, the merchant may haveinstalled apparatus for reading the bar codes of products sold.Alternatively, each product may be identified by a code assigned by themerchant which is recorded at the time of sale. Such data is stored in ascan database 46 and could be migrated to the data repository 40. Inthis way, the record may also include a suitable goods or servicesidentifier, for example a product or service code to identify whichgoods or services were involved in the interaction.

The record may also include data such as the date and/or time at whichthe interaction between the customer and merchant took place and/or thecash value of the transaction.

The interaction data is migrated to the data repository 40, generally byway of daily updates or in real time. It is advantageous to cleanse,catalogue and validate the interaction data during migration of the datato the data repository, and this task could be performed by either themerchant or by a third party. Once stored in the data repository 40, thedata could be linked to other sources of data for subsequent retrieval,for example the census data 44, scan data 46, data from the merchantcustomer database 48, data from a merchant loyalty programme 50 and/orpromotion data 52 held by the merchant.

The data repository 40 could be maintained by a merchant oralternatively could be maintained by a third party. Updates to the datarepository could be carried out by the merchant directly, oralternatively the merchant could provide batched data to a third partyfor updating the data. Alternatively, a third party could be entrustedwith the task, of collecting the interaction data and migrating the datato the data repository.

Referring to FIG. 7, a graphical representation of a merchant isgenerated and is displayed on the screen display of a client workstation20. Where a merchant operates from a retail store, the graphicalrepresentation could include a graphical spatial representation of thestore 200. The graphical representation 200 could show the position ofthe door 202, service counter and cash register 204, and a number ofshelves 206 on which products are displayed. Where the merchant operatesfrom two or more retail stores, the graphical representation couldinclude spatial representations of each store and could also include alarge scale map of the geographical area in which the merchant's storesare located.

Where a merchant operates a casino or similar gaming venue, thegraphical representation could include a spatial representation of eachindividual room in the casino showing the layout of individual gamingmachines and stations. The representation could also include a largescale representation of the entire premises showing smallerrepresentations of individual rooms.

It will be appreciated that where a merchant operates a warehouse, therepresentations could show the layout of various goods stored by themerchant. Where the merchant provides services for example financialservices, the representations could include schematic representations ofthe different areas of services offered by the merchant.

The invention is arranged to superimpose a representation of the dataretrieved from the data repository 40 on the representation of thepremises of the merchant. As shown in FIG. 7, the invention displays arepresentation of sales occurring during a predetermined period. Netrevenue is indicated at 208 during the period and turnover during thesame period is indicated at 210.

The preferred representation 200 is arranged to display to a user anumber of key performance indicators (KPIs) in addition to or as analternative to revenue and turnover. These KPIs may include, forexample, sales, gross profit, net profit, gross margin return oninventory investment (GMROII), net margin return on inventory investment(NMROII), return on net asset (RONA), and/or loyalty sales data.

The preferred representation displays a contoured representation of aset of data values. The set of data values could comprise sales figuresfor individual products, gross profit on individual products, and so on.Each product group is represented as an individual data point and acontoured representation centred on each data point is generated. Datapoint 212, for example, represents tobacco sales and the data point ispositioned adjacent the location of tobacco products in the storeindicated at 214.

As described above, the invention could generate individual stillrepresentations such as that shown in FIG. 7. Alternatively, theinvention could generate a series of representations at time intervals,for example hourly time intervals. By overlaying subsequentrepresentations over earlier representations, the rate at which datavalues such as net revenue or turnover (image over a time period can beobserved, and customer buying patterns are readily apparent.

The system may also overlay text over the spatial representation. Forexample, different shelves in the store or different products on theshelves may be identified by labels. Other labels could include theproduct selling price, product sales during the proceeding hour; orother information meaningful to the user.

A merchant operating a service station, for example, may identify fromthe above representations the periods in which sales of pies and otherhot food is highest. By keeping warmers and shelves stocked in advanceof these peak periods, the merchant can meet the demand of customers andreduce wastage.

The same merchant may also observe from the representations that salesof newspapers follow a similar pattern to sales of stamps. This mayindicate to the merchant that sales of newspapers are correlated tosales of stamps. By positioning newspapers and stamps in close proximityto each other within the store, the merchant could increase sales ofboth products.

A merchant could initiate a promotional campaign in relation to aparticular product and then identify the effectiveness of the campaignby viewing the representations generated by the system.

In another form of the invention, the merchant could comprise atelecommunications service provider operating a telecommunicationsnetwork. The flexibility of mobile phones, their reducing cost, and thewide coverage now available has resulted in rapid growth in mobile phoneuse in many countries. A mobile phone user communicates with anothermobile phone user by linking into a mobile phone network operated by themerchant. Mobile phone networks typically comprise one or more mobilephone sites which are small low powered radio transmitting and receivingstations. Each mobile site services a limited geographic area known as acell. Each mobile site can only service a finite number of calls at anyone time.

When a mobile phone is powered up, it generally searches for thestrongest signal from a mobile site. The mobile phone is then registeredas being located within the cell covered by that mobile site. When amobile phone user leaves one cell and enters another, the new sitecovering the new cell takes over the phone call, enabling thecommunication to be maintained. This procedure is often referred to as“handover.”

Referring to FIG. 8, the merchant's cellular network comprises one ormore fixed mobile phone sites 300, for example 300A, 300B, 300C and300D. Each site 300 preferably comprises a small low powered radiotransmitting and receiving station or antenna which links a mobile phoneuser into the merchant's mobile phone network to connect or attempt toconnect mobile phone users with each other.

The merchant may also operate movable sites, for example 302 which inturn could comprise omni-directional antennae mounted on trucks. Groupsof sites 300 and 302 are preferably controlled by one or more basestation controllers 304, for example 304A and 304B. Each controller isarranged to activate or deactivate individual sites as required and isalso arranged to compile data representing the capacity and usage ofindividual sites. Each fixed site 300 and movable site 302 arepreferably reconfigurable and connections between the sites and eachcontroller 304 are also reconfigurable so that the merchant can activateor deactivate specific sites to reduce gaps in coverage, to reduceinterference between sites, and to follow the demand around.

Data representing interactions between merchants and customers ispreferably transferred by the base station controllers 304 to the datarepository 40. Data is then retrieved from the data repository andprocessed with the server 62 in the manner described above. Preferablythe data undergoes data staging where the data is scrubbed and/orcleaned and errors or anomalies are corrected.

The resulting data stored in the data repository 40 typically comprisesone or more records. Each record may include, for example, a merchantidentifier, a customer identifier, a cell and/or site identifier andother data such as the date and/or time at which the interaction betweenthe customer and merchant took place.

The data may also include values of one or more key performanceindicators or KPIs. Typical KPIs could include network capacity, thepercentage of capacity used, call volume, average length of currentcalls and/or instances and rates of connection failure.

The data is preferably migrated to the data repository 40 by way ofregular updates or in real time. The data repository could be maintainedby a merchant or alternatively could be maintained by a third party.Updates to the data repository could be carried out by the merchantdirectly, or alternatively the merchant could provide batched data to athird party for updating the data repository. Alternatively, a thirdparty could be entrusted with the task of collecting the interactiondata from the base station controllers 304 and migrating the data to thedata repository.

As described above, the data is displayed on a client workstation 20,preferably as a graphic representation of the data. Where the merchantoperates a telecommunications network, the graphical representationcould include a graphical spatial representation of the networkrepresented by a collection of mobile sites, each site serving ageographic area or cell.

FIG. 9 illustrates a typical graphical spatial representation 320 of themerchant. Site or cell locations are indicated for example at 310 and312. The representation also shows one preferred form representation ofthe data retrieved from the data repository. The representation 320preferably includes a series of contours representing the values of oneor more key performance indicators or KPIs. The preferred representation320 is arranged as contour lines around the site or cell locations inthe spatial representation of the merchant.

In some circumstances, it is desirable to combine or aggregate customerinteractions among two or more cells. Data relating to separate cells isoften combined prior to or during data capture, resulting in the loss ofsome data. In these cases, it may be desirable to aggregate two or morecells. One preferred form aggregation method includes combininginteractions involving cells 310, 312, 314, 316 and 318. Therepresentation 320 is generated from a single data point located at cell318.

An alternative representation 330 is illustrated in FIG. 10. The KPIvalues of cells 310, 312, 314, 316 and 318 are aggregated and theaverage KPI value of these sites is then calculated. Contouredrepresentation 330 is generated from a set of 5 data points, each datapoint centred on a respective site. Each data point has the average ormean value of the set of sites 310, 312, 314, 316 and 318.

Further preferred representations for displaying aggregated KPI sitevalues are described with reference to FIGS. 11 to 15. In each case, thesystem is arranged to show part of a merchant's network, particularlythe part of the network in use by customers located at a particularvenue, for example a sports event.

FIG. 11 illustrates a contoured representation 340 generated byaggregating all site values over an area indicated by outline 342. Therepresentation 340 could be generated from a single data point locatedat 344.

As shown at FIG. 12, in one preferred form of contoured representation350, the representation could be generated from a single data point 352representing the aggregate of individual sites located within the areashown in the representation 350. The representation 350 may identify theindividual sites which are being aggregated by displaying lines 354radiating from data point 352 to the position of each individual site.

Referring to FIG. 13, the representation 360 could include outline 362of the area over which the aggregation has taken place. The preferredrepresentation 360 is generated as a function of a single central datapoint 364. The representation may also include a schematic view of avenue, for example a sports station or sports field as indicated at 366.

Referring to FIG. 14, a preferred form representation 370 could includean outline of a venue 372, a central data point 374, lines 376 radiatingfrom a central point 374 to each site, and a schematic representation ofthe venue indicated at 378.

As shown in FIG. 15, the system may display representation 380 showing asimplified representation of the data. By clicking “zoom box” 382, theuser could be presented with a more detailed view of the data, forexample the views shown in FIGS. 11 to 14.

FIGS. 16 to 20 illustrate preferred forms of representations showingindividual cell sites and connections between cell sites.Representations could include for example the skeleton shown in FIG. 16,a “no new point” skeleton shown in FIG. 17, a convex hull shown in FIG.18, a combination convex hull and skeleton shown in FIG. 19, and “bones”shown in FIG. 20. It will be appreciated that different arrangements ofsites are more suitable for certain types of site coverage. For example,the convex hull shown in FIG. 18 is particularly suitable forrepresenting site coverage of a localised venue, for example a stadium,whereas the skeleton of FIG. 16 could be more suited to showingcellphone coverage over a more diverse geographic area.

Further forms of preferred representations are described with referenceto FIGS. 21 to 24. It may be desirable to display the aggregation ofseveral sites from a single data point but yet maintain the ability todisplay differences between site locations.

FIG. 21 illustrates one preferred form representation 390. Therepresentation is generated from a single data point 392 whichrepresents the aggregation of KPI values at three distinct cellphonesites. The positions of the sites are indicated by lines 394, 396 and398, extending radially from data point 392 to each site.

FIG. 22 shows a further preferred form representation 400 which iscentred on single data point 392. The circular representation of FIG. 21is essentially stretched in FIG. 22 along respective lines 394, 396 and398, depending on the length of each line which in turn represents theposition of each site.

A further preferred form representation 410 is shown in FIG. 23, inwhich the contour lines representing the cellphone sites are eachconnected at central data point 392.

Alternatively as shown in FIG. 24, representation 420 could be dividedinto sectors. The representation is centred around central data point392 with lines 394, 396 and 398 radiating outward from the data point.Sector lines 422, 424 and 426 are positioned between pairs of adjacentlines, and the representation is generated between these sector lines.Each sector preferably has a radius calculated as a function of thelength of individual lines 394, 396 and 398.

It will be appreciated that the contoured representations of theinvention could be applied to various types of electroniccommunications. For example, the system could display representations ofcommunications over an analog or digital cellular network, a land linesuch as a PSTN, a paging network or a satellite network. As is becomingincreasingly common, the system could also be arranged to display datarelating to digital communications, for example text messaging andInternet communications.

The telecommunication service provider often needs to ensure that thereare no gaps in the signal from site to site to enable continuouscoverage and service. On the other hand, the provider must also resolveinterference between sites, particularly in urban areas. The providermust also ensure that there are sufficient sites and cells in eachgeographic area to handle instances of high demand, for example sportsevents. Instances of high demand can lead to connection failure, such as“congestion” where a customer cannot make a connection and ‘dropout’where, a customer loses a connection during a call.

The invention provides a user-friendly system and method for thetelecommunication service provider to analyse the capacity and usage ofa network. The system enables a telecommunication service provider tomonitor periods and areas of high demand to enable the provider toreconfigure a network to cope with such demand.

It is becoming increasingly common for merchants to operate websites aspart of their business. FIG. 25 illustrates a block diagram of thepreferred Internet-based system 500 in which the present invention maybe implemented. The system is similar to that of FIG. 1 with theexception that the data repository 40 could be connected to the Internet26. The system further comprises customer and merchant workstations.There could be one or more customers 510, for example customers 510A,510B and 510C, which may each comprise a personal computer orworkstation as described above. Each customer 510 is interfaced to theInternet 26. As shown in FIG. 25, each customer 510 could be connecteddirectly to the Internet as shown with 510C with a suitable dial-upconnection or could be connected through a local area network or LAN asis the case with customers 510A and 510B which are connected to localarea network or LAN 512 connected to a network server 514 andcommunicate with the Internet 26 as shown.

The system also includes one or more web servers 520, for example webserver 520A and 520B. Each web server 520 is connected to the Internet26 as shown. Each web server 520 preferably comprises a personalcomputer or workstation operating under the control of suitablesoftware. Connected to web servers 520 are one or more merchantcomputers or workstations 530, for example merchant 530A, 530B and 530C.Two or more merchants could be connected to the same web server as isthe case with merchant 530A and 530B both connected to web server 520A.Alternatively, merchant 530C, for example, could be connected todedicated web server 520B.

The, merchant 530 could include an individual, a company or organisationand will typically operate a website or other electronic medium throughwhich customer 510 purchases goods or services. The merchant mayalternatively operate an on-line casino, gambling or other gamingfacility. The merchant could also offer transport and delivery,financial or banking services.

Customer 510 could include an individual, a company organisation. Thecustomer could be a purchaser of goods or services from the merchant orcould simply be visiting a web site operated by the merchant. Aninteraction between a customer 510 and a merchant 530 could be initiatedby either the customer or by the merchant. As the customer 510 interactswith merchant 530, the interaction generates interaction data which iscollected and stored in data repository 40.

Typical data records could include, for example, a merchant identifier.This merchant identifier could be used to identify a particular merchantand could comprise the universal resource locator (URL) of a web siteoperated by the merchant, or an Internet protocol (IP) address for themerchant.

The record could include a customer identifier. The customer identifiercould include the IP address or other network address of the customer510. The customer identifier could alternatively comprise a characterstring assigned to the customer by the merchant during a registrationprocess with a facility for the customer to supply a user name andpassword to initiate an interaction in the known way.

The record could also include the universal resource locator (URL) of aweb page visited by the customer 510 during an interaction. The recordcould include the date and/or time at which the interaction between thecustomer and the merchant took place, the cash value of any transactionif applicable, and a goods/services identifier where a transaction hastaken place. It is envisaged that each new URL visited by a customer,for example each new page visited in a merchant website, generates a newinteraction record. By retrieving and storing these records by date andtime, it is possible to calculate the number of customers visiting aparticular web site and the average time spent viewing a particular webpage or page cluster, as will be more particularly described below.

FIG. 26 shows a typical representation generated by the system. Thedisplay could include a customer provenance window 600. The preferredcustomer provenance window displays a graphical spatial representationin the form of a topological map. The map is arranged to show the originof customers interacting with a particular merchant. It will beappreciated that the scale of the map could be altered, depending on thecustomer base under consideration. The map could include a detailed map,such as that shown in FIG. 26 showing suburbs in a particular city,could alternatively show individual cities in a particular country, orcould be a global map showing all countries.

The interaction data from which the representation is obtained couldinclude a customer origin identifier. Alternatively, customer origindata could be stored in one or more further databases and indexed bycustomer identifier.

It is envisaged that a customer provenance representation could begenerated for any merchant customer application to which the system isapplied. For example, the merchant could operate in a commercialpremises or store, operate a wagering or betting service, a casino orother gaming facility, a car park, a telecommunications network or awebsite. The merchant could also offer a range of financial or insuranceservices. In each case the system could generate a customer provenancerepresentation. The customer provenance representation could begenerated as an alternative to or in addition to the representation ofthe merchant.

The system may present the data to the user based on one of a number ofkey performance indicators, or KPIs which could include total sales,gross profit, net profit, gross margin return on inventory investment(GMROII), net margin return on inventory investment (NMROII), return onnet asset (RONA), loyalty sales data, time spent viewing a particularwebsite and/or a web page visitation percentage. Each representationcould show, for example, a combination of a number of customers, thenumber of sales and gross profit, as is the case in FIG. 26.

The preferred representation of data displays a particular value at afinite set of data points spaced over the representation, for exampledata points 602A, 602B, 602C, 602D, 602E, 602F and 602G. The value ateach data point is preferably represented as a contoured representation,having a defined value centred on each data point with the values overthe representation dropping away between data points. Data points withlarge values, for example 602E, are presented as higher peaks than datapoints with lower values, for example 602G.

The customer provenance map 600 as shown in FIG. 26 illustrates that thecustomers contributing to the largest KPI values have a provenance orpoint from which they interact with a particular merchant which iscentred on point 602E. Customers contributing to the lowest KPI valuesfor the merchant have a provenance at point 602G. It will be readilyinferred from such a representation that the most valued customers arebased around point 602E.

Each interaction record generated by a merchant customer interactioncould include a customer identifier. This customer identifier could belinked to a physical address, within the requirements of any privacyrestrictions, provided to a merchant by a customer at the time ofregistration or log-on. Alternatively, a geographic location could beinferred from the interaction itself. For example, a customerworkstation used by a customer may use a particular network or Internetaddress from which a country code or indicator could be extracted. Thiswould at least provide customer provenance data to country level.

Referring to FIG. 26, the system could also generate and display arepresentation of the merchant as indicated at 610. Where a merchantoffers a range of goods or services, the representation 610 couldcomprise a graphical spatial representation of a “virtual store” similarto the store described above with reference to FIG. 7. The virtual storeplan could show virtual positions of doors, service counters and shelveson which products are displayed. Where a merchant operates in acommercial premises or store in conjunction with a web site, it isenvisaged that the representation 610 could comprise the actualgraphical spatial representation of the store. Where a merchant operatesfrom two or more retail stores, the graphical representation couldinclude spatial representations of each store and could also include alarge scale map of the geographic area in which the merchant's storesare located.

The representation 610 preferably shows distinct product types spaced,over the representation. As described above, each interaction record mayinclude a goods/services identifier which could identify a product type.Each product type or grouping in the representation could represent adata point which is contoured in the same way as the customer provenancemap 600 described above. Typical store plan data points are indicated at612A, 612B and 612C. KPI values at individual points 612A, 612B and 612Care displayed as peaks, and values, of areas between these data pointsare shown as contours in the same way as that described above.

The display could also include a progress bar as indicated at 620. Theprogress par 620 could include a time display 622 and date informationfor a particular visualisation. The presentation could also display oneor more KPIs, for example the number of customers, number of sales andgross profit for a particular visualisation and also display totals,cumulative totals and cumulative percentages.

It is envisaged that the representation shown in FIG. 26 could bepresented to, a user as a still image or as an animated visualisation orAVI. The time display 622 would show the user the progress of the AVI.It is also envisaged that the main screen could include progress barsindicated at 624 which present a sliding scale of cumulative KPI totalsto a user as the animation progresses.

The system is preferably also arranged to display a graphical site mapof a merchant's web site. FIG. 27 illustrates one preferred formrepresentation. Web site pages or page clusters are indicted, forexample as boxes 630A, 630B, 630C, 630D, 630E and 630F. Each box ispreferably shown with a page or page cluster number and a percentagerepresenting the percentage of users visiting the web site who haveviewed the particular page or page cluster. The user could also bepresented with a legend 632 for shading relating to particularpercentage values of visitation for each web page or page cluster.

For example, 100% of users visiting the web site have visited the homepage shown as 630A. Web page 630B, which is accessible from web page630A, has been visited by 28% of customers who visited page 630A. Webpage 630C, which is accessible from web page 630A, has been visited by71% of users. By retrieving a set of records from the data repository 40using a customer identifier as a key, and then sorting these records bydate and time, the usage of a web site by an individual customer can betracked and displayed in accordance with the invention.

In a preferred form, the representation shown in FIG. 27 could havesuperimposed on it a representation of the data retrieved from the datarepository in the form of a series of ripple contours, with those webpages attracting high usage being contoured as peaks. It will beappreciated that the KPI on which the representation is contoured couldinclude any one or more of the KPIs discussed above, for example totalsales, gross profit, net profit and the like.

Referring to FIG. 28, the system may also be arranged to show trafficflow associated with a nominated page or page cluster. The user may bepermitted to click for example on the representation of page 630D in thegraphical representation shown to the user, causing this page to behighlighted. Contributing pages 630B and 630C are highlighted as aredestination pages 630E and 630F. The remaining web pages are preferablygreyed out. Customer traffic flow between web pages is preferably shownproportionally by the size of linking arrows. For example, the arrowlinking web page 630B to 630D is thinner than the arrow linking web page630C to 630D, indicating that web traffic from web page 630C to 630D isgreater than web traffic from web page 630B to 630D. It is envisagedthat the colour of the arrows could also be varied to represent trafficflow.

The system is also preferably arranged to calculate and display web siteusage patterns. By retrieving a set of records from the data repository40 using a customer identifier as a key, and sorting the records by dateand time, the system can calculate how long a particular customer spendsviewing a particular web page or URL by calculating the difference intime between successive interaction records involving different webpages or URLs.

By compiling these usage patterns for individual customers, the systemcan develop and display a profile of site usage, for example as shown inFIG. 29 in which a merchant operates a web site having four web pages orpage clusters. These could include for example a front page or menu 640,a second web page 642 which elicits from the customer a customisedshopping list, a third web page 644 providing delivery and/or paymentoptions, and a fourth web page 646 arranged to display specials to acustomer and permit the customer to select one or more of thesespecials.

The system may recognise several patterns in site usage. For example, afirst pattern could comprise 31% of all users who spend between 5 and 20seconds viewing web page 640 and then exit. In a second pattern, 12% ofall users could spend between 3 and 10 seconds on web page 640, between0.5 and 5 minutes on web page 642, between 10 and 25 seconds on web page644 and then exit. Pattern three could comprise 7% of users who spend 3to 10 seconds on web page 640, 1.5 to 3 minutes on web page 642, spend 3to 12 minutes on web page 646, spend 10 to 20 seconds on web page 644and then exit.

The system could recognise these patterns of repeated web page and pagecluster visitation and usage. It could rank these patterns based on thepercentage of web site visitors that the pattern includes, and displaydetails such as the pattern percentage, the average time spent at eachpage or page cluster as indicated at 650, and the resultant KPIs ofdifferent usage patterns. The system could display, for example, afinite number of most common usage patterns, the number being defined bythe user.

The system could also be arranged to record and display further patternsof use of particular web pages. It is envisaged that the data repository40 could be arranged to store further interaction data, for example theareas of a web page from which a particular customer makes selections orinto which a customer types data, the areas to which a mouse pointeroperated by customer is tracked and clicked while in the web site, andalso the URL(s) of the source web page visited by a customer prior tovisiting the web page under consideration, known as the click source,and/or the destination web page visited by the customer after visitingthe web page under consideration.

The system may also be arranged to perform customer loyalty andmarketing functions. The user could be provided with several options forgenerating mailing lists of web site users according to a particularcriteria. For example, the system could generate a mailing list forthose customers who have used the site, or those customers who fit aparticular pattern of site usage as described above. The system couldidentify regular users of the site, calculate an approximate frequencyof site usage, identify trends of increasing or decreasing usage acrosssubsequent visits, and/or produce a list of those whose site usagechanges for some reason. For example, the system could identify weeklyshoppers who miss a week's order, customers who browse the ‘weeklyspecials” page, customers who have started to visit a particular webpage after being included in a promotional mailout, and whether thecustomer is making purchases as a result. The system could also bearranged to assemble mailing lists of those users who make heavy usageof help pages.

The invention assists a merchant to examine data relating to customersvisiting a web site operated by the merchant. The user may make sense ofand obtain useful data and from this data may identify optimal orderingof web page links on a merchant web site and select the most desirableordering and positioning of these links. The user may also identifycorrelations between sales of different goods or services and may alsoidentify the effectiveness of loyalty programmes and other incentiveschemes.

Banking organisations are one example of merchants who collect enormousquantities of data concerning all aspects of their business operations.A banking organisation may want to monitor automatic teller machines orATM usage and servicing in a city, what types of transactions arehappening at different times of the day, or to look at bank branch usagepatterns to justify the branch's existence. When a banking organisationwishes to launch a product or service into a new market, it would behelpful for the bank to be able to get a reliable model of theirpotential market penetration, and the probable makeup of thatpenetration model.

FIG. 30 illustrates one example of a display generated by the system fora merchant such as a banking organisation. One preferred representationincludes a customer provenance window 700, which, shows, for example,the location of double-income couples with no children. Suburbs withhigh numbers of these mortgages are shown as indicated at data points702 and 704.

The representation may indicate to a user that there is a markeddifference in concentration of such mortgages in different suburbs, eventhough demographic data may show that these suburbs have similardemographic profiles. This would indicate to a user that a bankingorganisation has lower than expected penetration of a mortgage productin that particular suburb, thereby revealing a business opportunity. Therepresentation shows that mortgage products have been sold moresuccessfully to households in the suburb of East Uptown as indicatedgenerally at 706 than in West Uptown as indicated generally at 708,despite the two suburbs having very similar demographic compositions. Inthis way, visualisation of a bank's customer base can be used in siteanalysis, whereby new sites are considered for opening branches orexisting marginal sites require justification for continued operation,and for targeted marking campaigns.

FIG. 31 illustrates a further example of the display generated for abanking merchant. The representation 710 preferably comprises a floorplan of a bank branch including representations of different businessunits for example foreign exchange 712, tellers 714A and 714B, enquiriesdesk 716, manager's office 718, personal loans 720, fast-drop box 722and ATM machine 724.

The representation 710 could be contoured on one of a number of KPIs.One KPI could be gross turnover which would indicate how each businessunit is performing. Contouring on other types of transactions would showthe different types of transactions which tend to occur at differenttimes of the day. This would enable a banking merchant to measure theperformance of different business units and branches and matchspecialist staff more closely to a bank customer's business needs.

It is envisaged that the invention will also have application forinsurance companies. An insurance company may wish to review itsbusiness performance data, for example to assess a potential client'srisk or to review premium levels. If the insurance company wishes tolaunch a product or service into a new market, it would be useful to beable to get a reliable model of the insurance company's potential marketpenetration, and the probable makeup of that penetration model.

The system could generate a visualisation showing a contouredrepresentation depicting some KPI, for example the number or value ofclaims or the cost to the company. For example, the company could createa visualisation with various burglary statistics contoured on it, withconcentrations of burglaries displayed as red “hot spots”, and areasthat suffer few or no burglaries being contoured in a neutral colour.The insurance company could use the summary information in thevisualisation to help assess the risk of providing home and contentsinsurance. to customers living in those areas.

The system could visualise how different events have impacted onprofits, insurance claims or uptake of products. For example, an eventsuch as an advertising campaign that is promoted in a particular region,or a shift in police focus towards investigating more burglaries orarsons would impact upon the company profitability. The impact of theseevents could be summarised in a contoured visualisation.

The system could show uptake of the merchant's services and products,and visualise the results of in-depth marketing, queries and analyses.For example, the system could produce a visualisation of those customerswho started policies and soon afterwards made insurance claims, or howchanges to services for example police or fire service coverage, haveimpacted on uptake of products or claims on policies.

Referring to FIG. 32, the system could show a customer provenance map750 of customers who have made claims on their home and contentsinsurance during a certain period, with the size of the claim contouredas a data value. Data points indicated at 752 and 754 indicate highnumbers and values of claims in certain areas.

It is also envisaged that the system perform and visualise predictivemodelling of the potential penetration into a new market, based on thedemographics of the merchant's existing customer base. This is achievedby evaluating the demographic makeup of the existing customer base,assessing the demographic makeup of .the new market, and extrapolatingthe data to produce the estimate. For example, if 15% of young men witha job who own a car worth between $5,000 and $8,000 currently insuretheir car with the merchant insurance company, then in the new marketabout 15% of young men with the same profile are likely to insure theircar with the insurance company.

Another area of application of the system is in the analysis ofmanufacturing operations. Manufacturers require their facilities to beat capacity usage in order to maximise the return on investment in theirbusiness. For any process in manufacturing, a delay or bottleneck atsome point in that process will hamper subsequent stages and lower theefficiency of the whole operation. It would be beneficial to enable amanufacturer to summarise and monitor the entire and/or particularaspects of a manufacturing operation; to ensure that the operation isworking to capacity at all times.

FIG. 33 illustrates one example of a visualisation based on the layoutof a manufacturing or other workspace. The representation 800illustrates the various stages involved in processing a sheepskin.Non-processed sheepskins indicated at 802 are washed at step 804. Thewashed sheepskins are then buffed at 806 and tanned at 808. The tannedskins are then stored at 810, dried in a drying room at 812 and thenpacked and shipped indicated at 814.

In representation 800, the number of sheepskins processed at eachparticular stage of the manufacturing operation comprises a data valueand is contoured. It is readily apparent that the tanning room 808 inFIG. 33 is processing fewer sheepskins than the buffing room 806 canproduce for it. Such a visualisation could draw to the attention of themanufacturer the operations of the tanning room so that appropriateaction can be taken, for example staff or resource reallocation.

The system can produce an efficiency analysis of different areas of theproduction process, and can assess proposed changes to the manufacturingoperation. This application could also assist with staff rotation aftermeasuring their performance.

In a further preferred form of the invention, the data repository isarranged to store a sports database of data representing one or moresports events. It is becoming increasingly common to collect largevolumes of data each time a game of sport is played. For example, a gameof rugby union generates statistics such as the total number of pointsscored, the number of tries scored and the number of tries scored whichare then converted. Other statistics include ball possessionrepresenting the proportion of the game during which a particular teamhad possession of the ball.

There is an increasing trend towards analysis of collected data with aview to analysing opponent's strategies and as a coaching aid inassessing the strengths and weaknesses of a particular team. It is alsoespecially desirable with televised sports to present the collected datato spectators in a form which is easily interpreted.

FIG. 34 illustrates a preferred form database schema 900 suitable formaintaining sports data in the data repository 40. The schema 900 isshown as a single table in a relational database. It will be appreciatedthat this table could be normalised to an appropriate extent. It willalso be appreciated that schema 900 could alternatively be representedin an object-oriented form.

The schema 900 shown in FIG. 34 is particularly suitable for storingdata representing possession and territory in a rugby game. A typicalrecord represents a time slice and may include, for example, a recordidentifier 902. The schema 900 may also include game identifier 904 touniquely identify the particular sports event represented. The schema900 may also include a possession field 906 which indicates which teamis in possession of the ball in a particular time slice, a time and/ordate indicator 908 and a half field 910 representing the half of thegame represented by a time slice.

The schema may also include geographic co-ordinates. The geographicco-ordinates Shown in FIG. 34 include X co-ordinates 912 and Yco-ordinates 914 representing the geographic position of the rugby ballon the field in a particular time slice in the New Zealand Map Grid(NZMG) Local Co-Ordinate System Notation. It is envisaged that thegeographic co-ordinates could alternatively be represented in AustralianMap Grid (AMG) notation or as a latitude or longitude.

FIG. 35 illustrates a representation 950 showing a plan view of a rugbyfield showing boundary lines 952, territory lines such as the 22indicated at 954 and the halfway line indicated at 956. Therepresentation 950 may also include goal posts 958 and 960. Therepresentation 950 is an example of the sports venue or playing field onwhich the rugby game is played.

As shown in FIG. 35, the system is arranged to display a contouredrepresentation of the data retrieved from the data repository 40. It isenvisaged that the contoured representation could be superimposed ontographical representation 950 as shown in FIG. 35. Alternatively, thecontoured representation could be displayed adjacent to therepresentation 950, or as an alternative to the representation 950.

The preferred representation 950 is divided into a plurality or grid ofareas. The number and spacing of these areas will in each case depend onthe result desired. Smaller grid areas will result in a more detailedrepresentation whereas larger grids will result in a less detailedrepresentation. In one preferred form, the total time that the ball islocated in a particular area during a rugby game is calculated from dataretrieved from the data repository 40. In the contoured representationof FIG. 35, the location of the ball throughout the game can berepresented with X and Y values being the geographic co-ordinates of therugby ball and the Z value being the total time, or a percentage orportion of the total time, that the rugby ball is located at point(X,Y).

As shown in FIG. 35, the points shown at 962, 964 and 966 respectivelyindicate geographic locations in which the ball is located repeatedlyduring the game and areas such as 968 indicate areas in which the ballwas not located at all, or not located to a noticeable extent, during agame.

It is envisaged that the contoured representations could be shown assingle summary frames or stills or could alternatively be represented asa series of frames in an animated sequence or AVI. It will also beappreciated that the user may be provided with a query facility toselect desired frames to display. Where an animated sequence ispresented to the user, the user could be provided with the ability toselect an appropriate time period to view and also be provided with thefacility to control the rate or speed at which a sequence is displayedto the user.

It is envisaged that the nature and scope of data representing a sportsevent and the contoured representation of the data could be varied. Forexample, a contoured representation could be produced of ball possessionduring a rugby game. The ball possession of a particular team could beobtained by summing each time sequence in the data repository from thetime a team acquires possession of the ball to the time the team losespossession. It will be appreciated that the database schema 900 couldinclude one or more fields representing the nature of play in aparticular time, for example a scrum, maul, charge, line-out, mark,penalty or conversion. Furthermore, the magnitude and direction ofchange in the geographic position of the ball could be used to calculatethe effectiveness of a scrum, maul or charge.

The system could additionally or alternatively be arranged to store indata repository 40 other statistics and key performance indicators. Forexample, team KPIs could include the score, amount of possession,territory, the number of penalties conceded, scrums or mauls that arewon or lost, and line-outs that are won or lost. Individual player KPIscould include points scored, tackles made both successful andunsuccessful, handling errors, breaks or half breaks, yards gained in acharge, kicks/passes and runs, turnovers, passes and tackles, penalties,dropped ball as a percentage per game for a pass or from a kick andcharge downs.

The system could also store and present KPI groups such as a generaloverview, a first ⅝ view, forward view, loose view, back view and/oroutside back view.

The system may also store other KPIs such as the number of kicks in agame, weather factors such as wind speed and direction, rain, sleet orsnow, representations of the particular grass or soil, the captain andcoach of a particular team in a particular game, and the nature of game,whether it is a local or international challenge or whether it is asemi-final or final.

FIGS. 36 to 38 illustrate further representations which could bepresented to a user in relation to a sports event.

FIG. 36 illustrates ball possession of each team in a rugby game and theposition on the field in which possession is secured.

FIG. 37 illustrates one preferred form of displaying breaks in a game.The width of the arrows indicates the number of breaks and the locationon the field in which the arrow is placed. Where the display isanimated, the arrows could fade with time to illustrate ball play.Various other features of a rugby game can be represented in a visualmanner by the use of graphical images. The size of each image indicatesthe number of instances of a particular game feature which have occurredin that location.

FIG. 38 Illustrates rucks and/or mauls represented by a series of dots.It is envisaged that dots and other symbols could be used to representother gaming features, for example line-outs, penalties awarded, errors,turnovers and combinations such as missed penalties and kicks for touch.

FIG. 39 illustrates a preferred method of data acquisition arranged tocapture data for storage in and subsequent retrieval from the datarepository 40. Actual footage of a recorded rugby game could bedisplayed in a game window (not shown) on a display device. A graphicalrepresentation of a venue is displayed in window 970. The representationshown in 970 is divided into a grid, each element in the gridrepresenting a geographic location at the sports venue.

A user views video footage in the game window and notes the position ofthe ball at a particular time. As the ball is moved around the playingarea, the user operates a pointing device such as a mouse, trackball,joystick or other suitable device to alter the position of cursor 972 inwindow 970. The position of cursor 972 is automatically recorded and thecorresponding geographic position of the ball on the playing field iscalculated from the position of the cursor 972 in window 970. In thisway, the position of a ball through a game can be calculated.

It is envisaged that this data acquisition could be at least partiallyautomated. For example, the location of the rugby ball in a plurality oftime slices could be calculated using known image processing techniques.Successive images of the rugby field could be analysed and the ballidentified in the images from the shape and/or colour of the ball.

The data acquisition steps could be further supplemented by manualtechniques such as individuals viewing the game and keeping statistics,or by automated techniques such as by tracking movement with a suitableGPS system.

The data repository 40 could be arranged to store demographic playerprofiles, including for example age, weight, tackles made, tries scored,total number of runs, number of times over the advantage line, whetheror not runs lead to turnover, instances of dropped ball, instances ofisolation, successful pass/handoffs, type of run preferred (kick andchase vs break), total yardage gained in the run, and field position.The database could also store data on injuries, development, teams,referees and/or coaches.

It will be appreciated that the contoured representations describedabove could be applied to a plurality of sports. With appropriatemodification of the database schema, graphical representation of thesports venue, and the contoured representation, the system could beapplied to sports such as rugby league, soccer, tennis, golf, grid iron,baseball, softball, Aussie Rules, hockey, ice hockey and basketball. Thesystem could also be applied to track and field athletics events andalso horse and dog racing.

The invention provides a user-friendly system suitable in the field ofsports analysis, for analysis of opposing teams, for use as a coachingaid, and for live viewing for spectators. Preferred forms of theinvention may perform player profiling, track game development, pinpointthe circumstances leading to a player's injury, and assist coaches andsports management with assessing referee performance.

In a further preferred form, the merchant's business could involvereservation of products or services for use by the customer, such ascarparking, boat moorings, secondary and tertiary course allocation,seminar event or course bookings and plane, boat and train bookings.Owners of carparking buildings, for example, require maximum utilisationof available space in order to maximise profits. Such merchantsinevitably run below maximum capacity, even in environments where thereis a heavy demand for their service, as some places that are bookedand/or paid for are often not used. For example, the prepaid carparks ina carparking building will probably not all be used on any given day,due to work sickness, out of town trips, annual leave and the like.

The data repository 40 could be arranged to store data relating to forexample carparking buildings. This data could include percentage ofoccupation, the length of stay, the time of arrival and departure, andpreferred position. The system could be arranged to display the merchantpremises and superimpose the data values in the form of contouredrepresentations.

FIG. 40 illustrates one example of a display 980 generated by the systemwhere the merchant is a carpark operator. The display 980 preferablycomprises a floor plan of the car park building. Individual car parksare shown, for example, at 982 and 984, with corresponding contouredrepresentations indicated at 986 and 988.

Where such visualisation identifies a time period for a facility withconsistently low occupation, the merchant can target the market to boostoccupation or to lure competitor's customers. For example, a carparkingbusiness that identifies an evening with consistently low buildingoccupation may offer a cheap parking movie ticket deal with a nearbycinema complex.

The system enables a merchant to optimise returns by revealing theweekday and time of year and the like when facilities can be oversold,and the margin by which they may be oversold. For example, if a parkingbuilding has 120 parks, the system may reveal they are able to sell 135prepaid parks during the winter, and 128 prepaid parks during thesummer, and then after a particular time of day, for example 9:30 am,they can sell any remaining empty prepaid parks to casual parkers. Thedata visualisation may also reveal that on winter Mondays the merchanthas far more empty prepaid parks than any other day of the week, whichthe merchant could then market to casual parkers.

It will be appreciated that the uses and potential areas of applicationof the system are wide and varied. Merchants and other organisations donot need to follow the traditional approach of forming a hypothesis inadvance and then verifying the hypothesis, although the representationsgenerated by the system may be useful for verifying a particularhypothesis. The system presents data in an easily interpreted andintuitive manner may be useful in identifying unexpected trends in thedata. The foregoing describes the invention including preferred formsthereof. Alterations and modifications as will be obvious to thoseskilled in the art are intended to be incorporated within the scopehereof as defined by the accompanying claims.

1. A method of data visualisation comprising: maintaining in a datavalue memory a finite set of data values; displaying a representation ofeach data value centered on respective data points; and generating anddisplaying a representation having a cross-sectional shape of abell-shaped curve using a processor such that each data point isdisplayed as an apex of the bell-shaped curve.
 2. A method of datavisualisation of claim 1, further comprising: maintaining in a memory aninteraction database of interaction data representing interactionsbetween customers and merchants; retrieving from the interactiondatabase data representing interactions between customers and merchants;constructing the finite set of data values from the retrieved data; andstoring the data values in the data value memory.
 3. A method of datavisualisation of claim 2, wherein the merchant operates from one or morecommercial premises, the method further comprising displaying agraphical spatial representation of the premises of the merchant.
 4. Amethod of data visualisation of claim 3, wherein the merchant sells arange of products to customers, each product having a product code, themethod further comprising maintaining a product code for eachinteraction in the interaction data.
 5. A method of data visualisationof claim 3, wherein the merchant operates a casino or gaming venuecomprising one or more stations, each station having a stationidentifier, the method further comprising maintaining a stationidentifier for each interaction in the interaction data.
 6. A method ofdata visualisation of claim 3, wherein the merchant comprises a wageringor betting service provider, the method further comprising maintaining awager or betting service provider, the method further comprisingmaintaining a merchant identifier and a monetary value for eachinteraction in the interaction data.
 7. A method of data visualisationof claim 3, wherein the merchant comprises a financial or insuranceservices provider comprising one or more business units, each businessunit having a business unit identifier, the method further comprisingmaintaining a business unit identifier for each interaction in theinteraction data.
 8. A method of data visualisation of claim 3, whereinthe merchant provides reservation of products or services, the methodfurther comprising maintaining a merchant identifier and the time of theinteraction for each interaction in the interaction data.
 9. A method ofdata visualisation of claim 1, further comprising: maintaining in amemory a manufacturing process database of data representing one or moremanufacturing processes; retrieving from the manufacturing processdatabase data representing a manufacturing process; constructing thefinite set of data values from the retrieved data; and storing the datavalues in the data value memory.
 10. A method of data visualisation ofclaim 9, wherein the manufacturing process comprises one or moremanufacturing stages, each stage having a stage identifier, the methodfurther comprising maintaining a stage identifier for each interactionin the interaction data.
 11. A method of data visualisation of claim 2,wherein the merchant comprises a telecommunications service provideroperating a telecommunications network, the display further arranged todisplay a graphical spatial representation of a network or part of anetwork operated by a merchant.
 12. A method of data visualisation ofclaim 2, wherein the merchant operates from one or more web sites whichare accessed by customers over a computer network, the display furtherarranged to display a graphical representation comprising a graphicalweb site map of a merchant.
 13. A method of data visualisation of claim2, wherein the display means is further arranged to display an area mapshowing the origin of customers in merchant customer interactions.
 14. Amethod of data visualisation of claim 1, further comprising: maintainingin a memory a sports database of data representing one or more sportsevents; retrieving from the sports database data representing a sportsevent; constructing the finite set of data values from the retrieveddata; and storing the data values in the data value memory.
 15. A methodof data visualisation of claim 14, further comprising: displaying agraphical representation of a sports venue at which the sports event isheld; and superimposing the contoured representation of the data valueson the graphical representation of the sports venue.
 16. A method ofdata visualisation comprising: accessing a finite set of data values;displaying a representation of each data value centered on respectivedata points; and generating and displaying a representation having across-sectional shape of a bell-shaped curve using a processor such thateach data point is displayed as an apex of the bell-shaped curve.
 17. Amethod of data visualisation of claim 16, further comprising:maintaining in a memory an interaction database of interaction datarepresenting interactions between customers and merchants; retrievingfrom the interaction database data representing interactions betweencustomers and merchants; constructing the finite set of data values fromthe retrieved data using a processor; and storing the data values in thedata value memory.
 18. A data visualisation system comprising: a datavalue memory in which is maintained a finite set of data values; adisplay arranged to display a representation of each data value centeredon respective data points; and a contour generator arranged to generateand display a representation having a cross-sectional shape of abell-shaped curve in which each data point is displayed as an apex ofthe bell-shaped curve.
 19. A data visualisation system as claimed inclaim 18, further comprising a memory in which is maintained aninteraction database of interaction data representing interactionsbetween customers and merchants; and a retrieval device arranged toretrieve from the interaction database data representing interactionsbetween customers and merchants, to construct the finite set of datavalues from the retrieved data and to store the data values in the datavalue memory.
 20. A data visualisation system as claimed in claim 19,wherein the merchant operates from one or more commercial premises, thedisplay further arranged to display a graphical spatial representationof the premises of the merchant.
 21. A data visualisation system asclaimed in claim 20, wherein the merchant sells a range of products tocustomers, each product having a product code, the interaction datacomprising a product code for each interaction.
 22. A data visualisationsystem as claimed in claim 20, wherein the merchant operates a casino orgaming venue comprising one or more stations, each station having astation identifier, the interaction data comprising a station identifierfor each interaction.
 23. A data visualisation system as claimed inclaim 20, wherein the merchant comprises a wagering or betting serviceprovider, the interaction data comprising a merchant identifier and amonetary value for each interaction.
 24. A data visualisation system asclaimed in claim 20, wherein the merchant comprises a financial orinsurance services provider comprising one or more business units, eachbusiness unit having a business unit identifier, the interaction datacomprising a business unit identifier for each interaction.
 25. A datavisualisation system as claimed in claim 20, wherein the merchantprovides reservation of products or services, the interaction datacomprising a merchant identifier and the time of the interaction foreach interaction.
 26. A data visualisation system as claimed in claim18, further comprising: a memory in which is maintained a manufacturingprocess database of data representing one or more manufacturingprocesses; and a retrieval device arranged to retrieve from themanufacturing process database data representing a manufacturingprocess, to construct the finite set of data values from the retrieveddata and to store the data values in the data value memory.
 27. A datavisualisation system as claimed in claim 26, wherein the manufacturingprocess comprises one or more manufacturing stages, each stage having astage identifier, the interaction data comprising a stage identifier foreach interaction.
 28. A data visualisation system as claimed in claim19, wherein the merchant comprises a telecommunications service provideroperating a telecommunications network, the display further arranged todisplay a graphical spatial representation of a network or part of anetwork operated by a merchant.
 29. A data visualisation system asclaimed in claim 19, wherein the merchant operates from one or more websites which are accessed by customers over a computer network, thedisplay further arranged to display a graphical representationcomprising a graphical web site map of a merchant.
 30. A datavisualisation system as claimed in claim 19, wherein the display isfurther arranged to display an area map showing the origin of customersin merchant customer interactions.
 31. A data visualisation system asclaimed in claim 18, further comprising a memory in which is maintaineda sports database of data representing one or more sports events; and aretrieval device arranged to retrieve from the sports database datarepresenting a sports event, to construct the finite set of data valuesfrom the retrieved data and to store the data values in the data valuememory.
 32. A data visualisation system as claimed in claim 31, whereinthe display is further arranged to display a graphical representation ofa sports venue at which the sports event is held and to superimpose thecontoured representation of the data values on the graphicalrepresentation of the sports venue.